Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2024-02-05 Cooperative journals: 《中国全科医学》
Abstract： Background In recent years，in the context of global aging，the number of patients with chronic diseases in China has increased significantly，and the the coexistence of multiple diseases has become more and more common，which seriously threatens the life safety and quality of life of the older adults in China. Objective To investigate the status of multimorbidity of older adults，and explore the relationship and pathways of action between sleep，physical activity，social network and multimorbidity of older adults，providing ideas for the effective prevention of multimorbidity and health improvement of older adults. Methods Elderly people aged ≥ 60 years in the Community Health and Behavior of the Elderly Panel Study（CHBEPS）established by our team were selected as the subjects of the survey，a questionnaire was used to investigate the study population，the research objects were investigated by questionnaire，and the general situation was collected by self-designed basic information collection form，IPAQ-S-C，LSNS-6 and PSQI were used to assess the physical activity，social network and sleep of the subjects. AMOS 28.0 statistical software was used to set up the structural equation model. Results A total of 3 392 valid questionnaires were collected from 3 531 people over 60 years old，with an effective recovery rate of 96%. The average score of physical activity was（2 426.42±3 053.09）Met-min/w，the average score of social network was（15.91±6.43），and the average score of sleep was（5.49±3.53）. There were 788（23.23%）older adults with insufficient social network and 353（10.41%）older adults with fair or very poor sleep quality. The prevalence of multimorbidity among the survey respondents was 41.13%（1 395/3 392）. The results of correlation analysis showed that social network was negatively correlated with sleep level（r=-0.113，P<0.01）and multimorbidity（r=-0.049，P<0.01），and was positively correlated with physical activity（r=0.073，P<0.01）. Multivariate Logistic regression analysis showed that physical activity of 0-600 MET-min/w（OR=0.576，95%CI=0.342-0.970）and good sleep quality（OR=0.409，95%CI=0.209-0.803）were protective factors for multimorbidity（P<0.05）. The results of structural equation modeling showed that social networks could affect physical activity and sleep quality（standardized path coefficient =0.096，t=4.982，P<0.001；standardized path coefficient=-0.043，t=-5.981，P<0.001），physical activity and sleep quality could affect multimorbidity（standardized path coefficient=0.023，t=5.280，P<0.001；standardized path coefficient=0.111，t=9.409，P<0.001）. Social network had no direct effect on multimorbidity，but an indirect effect on it through two mediators of physical activity and sleep. The indirect effect of social network on multimorbidity through physical activity accounted for 10% of the total effect，and the indirect effect of social network on multimorbidity through sleep accounted for 36.5% of the total effect. Conclusion The prevalence of multimorbidity is high in the older adults（41.13%）. The social network of the elderly group should be appropriately expanded to encourage them to maintain a moderate amount of physical activity and a good quality of sleep，alleviate and prevent the occurrence of multimorbidity.
Subjects: Medicine, Pharmacy >> Preventive Medicine and Hygienics submitted time 2024-02-19 Cooperative journals: 《中国全科医学》
LIAO Yanming
ZHENG Xiao
XUE Yaqing
XIAO Shujuan
XUE Benli
LI Xinru
CHEN Yiming
ZHANG Mengjie
ZHANG Chichen
Abstract： Background The severe trend of the aging population，the rapid increase in the prevalence of chronic diseases among older adults，and the greater prominence of multimorbidity have posed challenges to the prevention and treatment of chronic diseases in China. Adverse health-related behaviors are modifiable risk factors for chronic diseases. Exploring the latent classes of health-related behaviors in older adults with multimorbidity and their associations with quality of life will help identify the characteristics of their health-related behaviors and uncover risk behaviors affecting the quality of life，providing references for precise health management to improve the quality of life of older adults. Objective This study aimed to explore the latent classes of health-related behaviors in older adults with multimorbidity and the differences in the quality of life among the different classes，to provide references for conducting precise health management to improve the quality of life of older adults. Methods Based on the baseline data from the Community Health and Behavior of the Elderly Panel Study（CHBEPS）conducted by our team，a total of 1，395 older adults aged 60 years and above with multimorbidity were included as study participants. A self designed questionnaire was used to collect basic information，including disease status，smoking status，alcohol consumption，and dietary preferences of the participants. The Pittsburgh Sleep Quality Index（PSQI），International Physical Activity Questionnaire-Short-Chinese Version（IPAQ-S-C），and Lubben Social Network Scale-6（LSNS-6）were used to assess staying up late，physical activity，and social network of the participants，respectively. The EuroQol five-dimensional five-level questionnaire（EQ-5D-5L）was used to measure the quality of life of the participants. Latent class analysis of health-related behaviors among older adults with multimorbidity was conducted using Mplus 8.3 software. Based on the fitted model，the different latent classes of health-related behaviors among older adults with multimorbidity were used as groups，and the Kruskal-Wallis and Wilcoxon rank-sum tests were performed using SPSS 26.0 software to analyze the differences in quality of life among these groups. Results Four latent classes of health-related behaviors were identified among older adults with multimorbidity，which are named the health behavior group，risk behavior group，comprehensive behavior group，and adverse behavior group. There were statistically significant differences in quality of life among the four latent classes（P<0.05）. Specifically，the quality of life in the health behavior group was higher than that in the risk behavior group and adverse behavior group（P<0.05）. Conclusion When implementing precise health management for older adults with multimorbidity，the characteristics of their health-related behaviors should be taken into account. Special attention should be given to those with a higher probability of behaviors such as smoking，alcohol consumption，and a preference for sweet，spicy，and salty tastes，as well as those with a lower probability of behaviors such as a balanced diet，regular consumption of vegetables and fruits，and social networks. Additionally，measures targeted at addressing common issues such as insufficient physical activity should be implemented to improve the effectiveness of health management and the quality of life of older adults with multimorbidity.
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